code: def generate_combined_pojo(glm_model, gbm_model):
      glm_pojo_src = get_embeddable_pojo_source(glm_model)
      gbm_pojo_src = get_embeddable_pojo_source(gbm_model)
  
      results_dir = pyunit_utils.locate("results")
      combined_pojo_name = combined_pojo_class_name(
          glm_model, gbm_model
      )
      combined_pojo_path = os.path.join(
          results_dir, combined_pojo_name + ".java"
      )
      combined_pojo_src = TEMPLATE % (
          combined_pojo_name,
          combined_pojo_name,
          glm_model.model_id,
          gbm_model.model_id,
          glm_pojo_src,
          gbm_pojo_src,
      )
      with open(combined_pojo_path, "w") as combined_file:
          combined_file.write(combined_pojo_src)
      return combined_pojo_name, combined_pojo_path
  
file_path: h2o-3/h2o-py/tests/testdir_generic_model/pyunit_pojo_import.py
imports: import h2o
  from h2o.estimators import H2OGradientBoostingEstimator, H2OGeneralizedLinearEstimator
  from tests import pyunit_utils
  import os
  import sys
  from pandas.testing import assert_frame_equal
label_desc: Use image node_id 2 for calling a global function with example usage: generate_combined_pojo(glm_model, gbm_model) and returns: combined_pojo_name,  combined_pojo_path